Frequency Control in Multi-Carrier Microgrids with the Presence of Electric Vehicles Based on Adaptive Neuro Fuzzy Inference System Controller

Subject Areas : Renewable energy

Seyed Ali  Seyed Beheshti Fini ¹ (Department of Electrical and Computer- Kashan Branch, Islamic Azad University, Kashan, Iran)
Seyed Mohammad  Shariatmadar ² (Department of Electrical and Computer- Kashan Branch, Islamic Azad University, Kashan, Iran)
Vahid  Amir ³ (Department of Electrical and Computer- Kashan Branch, Islamic Azad University, Kashan, Iran)

Received: 2022-01-04 Accepted : 2022-04-29 Published : 2023-11-22

Keywords: Microgrid, Electric Vehicle, fuzzy control, Frequency control, Adaptive Neuro Fuzzy Inference System, secondary frequency,

Abstract :

Nowadays, the use of renewable resources has increased because of fossil fuel price growth, resource shortage, and environmental pollution. This study investigates a microgrid composed of wind and solar systems with battery storage sources and flywheel, diesel generator, and multi-carrier energy systems (MCH) as combined electricity and heat (CHP). The microgrid frequency is controlled based on the gas network and its consumption peak. In a multi-carrier network, the load distribution in the gas network is simultaneously considered with the electric charge distribution. Besides, the frequency is controlled nonlinearly. On the other hand, the growing trend of producing and using electric vehicles has generated new loads on the electricity network. In this regard, if these loads are not properly managed to charge them, the network’s frequency deviations will increase and cause the collapse of the electricity network.Therefore, electric vehicles (V2G) are considered in microgrid frequency tuning operations through ANFIS adaptive fuzzy control method. In order to compare the proposed method in the simulations, a fuzzy controller is used. The results of the simulations are examined in five studies that express the optimal performance of the proposed method in reducing frequency deviations, strength against disturbances and resistance Uncertainties in the system. The proposed method also has a more stable output power in microgrid production resources.

References:

[1] T. Sun, J. Lu, Z. Li, D. L. Lubkeman, N. Lu, “Modeling combined heat and power systems for microgrid applications", IEEE Trans. on Smart Grid, vol. 9, no. 5, pp. 4172-4180, Sept. 2018 (doi: 10.1109/TS­G.20­1­7.26­52723).

[2] H. Wu, M. Shahidehpour, “A game theoretic approach to risk-based optimal bidding strategies for electric vehicle aggregators in electricity markets with variable wind energy resources”, IEEE Trans. on Sustainable Energy, vol. 7, no. 1, pp. 374- 385, Jan. 2016 (doi: 10.1109/TSTE.2015.2498200).

[3] G. Haddadian, M. Khodayar, M. Shahidehpour, “Accelerating the global adoption of electric vehicles– barriers and drivers”, Electricity Journal, vol. 28, no. 10, pp. 53-68, Dec. 2015 (doi: 10.1016/j.tej.20­15.1­1.0­1­1‌).

[4] A. Dán, C. Farkas, L. Prikler, “V2G effects on frequency regulation and under frequency load shedding in a quasi-islanded grid”, Proceeding of the IEEE/ PowerTech, pp. 1-6, June. 2013 (doi: 10.1109/PTC.2013.6­652­2­20).

[5] K. Knezović, S. Martinenas, P.B. Andersen, A. Zecchino, M. Marinelli, “Enhancing the role of electric vehicles in the power grid: Field validation of multiple ancillary services”, IEEE Trans. on Transportation Electrification, vol. 3, no. 1, pp. 201-209, March. 2017 (doi: 10.1109/TTE.2016.2616864‌).

[6] M. Singh, P. Kumar, I. Kar, “Implementation of vehicle to grid infrastructure using fuzzy logic controller”, IEEE Trans. on Smart Grid, vol. 3, no. 1, pp. 565-577, March ‌2012 (doi: 10.1109/TSG.2011.2172697).

[7] M. Datta, T. Senjyu, “Fuzzy control of distributed PV inverters/energy storage systems/electric vehicles for frequency regulation in a large power system”, IEEE Trans. on Smart Grid, vol. 4, no. 1, pp. 479-488, March. 2013 (doi: 10.1109/TSG.2012.2237044‌).

[8] H. Ali, G. Magdy, B. Li, G. Shabib, A.A. Elbaset, D. Xu, Y. Mitani, “A new frequency control strategy in an islanded microgrid using virtual inertia control-based coefficient diagram method”, IEEE Access, vol. 7, pp. 16979-16990, 2019 (doi: 10.1109/ACCESS.2019.2894840).

[9] D. Yu, H. Zhu, W. Han, D. Holburn, “Dynamic multi agent-based management and load frequency control of PV/Fuel cell/wind turbine/CHP in autonomous microgrid system”, Energy, vol. 173, pp. 554-568, April. 2019 (doi: 10.1016/j.energy.2019.02.094).

[10] M. Jayachandran, G. Ravi, “Decentralized model predictive hierarchical control strategy for islanded ac microgrids”, Electric Power Systems Research, vol. 170, pp. 92-100, May 2019 ‌‌(doi: 10.1016/j.epsr.201­9.0­1.0­10).

[11] K.W. Joung, T. Kim, J. Park, “Decoupled frequency and voltage control for stand-alone microgrid with high renewable penetration”, IEEE Trans. on Industry Applications, vol. 55, pp. 122-133, Jan/Feb. 2019 (doi: 10.1109/ICPS.2018.8369983).

[12] C.T. Hsu, T.J. Cheng, H.M. Huang, Y.D. Lee, Y.R. Chang, J.L. Jiang, “Over frequency control of photovoltaic inverters in an island microgrid”, Microelectronics Reliability, vol. 92, pp. 42-54, Jan. 2019 (doi: 10.1016/j.m­icro­rel.2018.11.011).

[13] X. Xu, W. Hu, D. Cao, Q. Huang, C. Chen, Z. Chen, “Optimized sizing of a standalone PV-wind-hydropower station with pumped-storage installation hybrid energy system”, Renewable Energy, vol. 147, pp. 1418-1431, March 2020 (doi: 10.1016/j.renene.2019.09.099).

[14] B. Farahmand, M. Dehghani, N. Vafamand, “Fuzzy model-based controller for blood glucose control in type 1 diabetes: An LMI approach", Biomedical Signal Processing and Control, vol. 54, Article Number: 101627, Sept. 2019 (doi:10.1016/j.bspc.2019.101627).

[15] J. Guo, “Application of full order sliding mode control based on different areas power system with load frequency control”, ISA Transactions, vol. 92, pp. 23-34, Sept. 2019 (doi:­ 10.1016/j.­isatra. 2019.01.036).

[16] J. Sharma, Y.V. Hote, R. Prasad, “PID controller design for interval load frequency control system with communication time delay”, Control Engineering Practice, vol. 89, pp. 154-168, Aug. 2019 (doi: 10.1016/­j.c­on­­engprac.2019.05.016).

[17] P.K. Ray, A. Mohanty, “A robust firefly–swarm hybrid optimization for frequency control in wind/PV/FC based microgrid”, Applied Soft Computing, vol. 85, Article Number: 105823, Dec. 2019 (doi: 10.1016/j.a­soc­.2019.105823).

[18] G. Agundis-Tinajero, J. Segundo-Ramírez, N. Visairo-Cruz, M. Savaghebi, J.M. Guerrero, E. Barocio, “Power flow modeling of islanded ac microgrids with hierarchical control”, International Journal of Electrical Power and Energy Systems, vol. 105, pp. 28-36, Feb. 2019 (doi: 10.1016/J.IJEPES.2018.08.002).

[19] F.O. Hocaoglu, O.N. Gerek, M. Kurban, “The effect of model generated solar radiation data usage in hybrid (wind–PV) sizing studies”, Energy Conversion and Management, vol. 50, pp. 2956-2963, Dec. 2019 (doi: 10.1016/j.enconman.2009.07.011).

[20] D. Qin, Q. Sun, R. Wang, D. Ma, M. Liu, “Adaptive bidirectional droop control for electric vehicles parking with vehicle-to-grid service in microgrid”, CSEE Journal of Power and Energy Systems, vol. 6, no. 4, pp. 793-805, Dec. 2020 (doi: 10.17775/CSEEJPES.2020.00310).

[21] U.C. Prusty, P.C. Nayak, R.C. Prusty S. Panda, “Impact of vehicle to grid mode electric vehicles in standalone microgrid for frequency regulation”, Proceeding of the IEEE/ISSSC, pp. 1-6, Gunupur Odisha, India, Dec. 2020 )doi: 10.1109/iSSSC50941.2020.9358834(‌.

[22] M. H. Khooban, T. Niknam, F. Blaabjerg, T. Dragičević, “A new load frequency control strategy for micro-grids with considering electrical vehicles”, Electric Power Systems Research, vol. 143, pp. 585-598, Feb. 2017 (doi: 10.1016/j.epsr.2016.10.057).

[23] S. Iqbal, A. Xin, M.U. Jan, S. Salman, A.U.M. Zaki, H.U. Rehman M.F. Shinwari, M.A. Abdelbaky, “V2G strategy for primary frequency control of an industrial microgrid considering the charging station operator”, Electronics, vol. 9, no. 4, p. 549, March 2020(doi: 10.3390/electronics9040549).

[24] H. Fan, L. Jiang, C.K. Zhang, C. Mao, “Frequency regulation of multi-area power systems with plug-in electric vehicles considering communication delays”,  IET Generation, Transmission & Distribution, vol. 10, no. 14, pp. 3481-3491, Nov. 2016 (doi: 10.1049/iet-gtd.2016.0108).

[25] W. Yan, L. Sheng, D. Xu, W. Yang, Q. Liu, “H_∞ robust load frequency control for multi-area interconnected power system with hybrid energy storage system”, Applied Sciences, vol. 8, no. 10, Article Number: 1748, Sept. 2018 (doi: 10.3390/ app8101748).

[26] Y. Xu, C. Li, Z. Wang, N. Zhang, B. Peng, “Load frequency control of a novel renewable energy integrated micro-grid containing pumped hydropower energy storage”, IEEE Access, vol. 6, pp. 29067-29077, April  2018 (doi: 10.1109/ACCESS.2018.2826015).

[27]  P. Ivanova, O. Linkevics, A. Sauhats, “Cost-benefit analysis of CHP plants taking into account air cooling technologies”, Proceeding of the IEEE/EEEIC, pp. 1-6, Milan, Italy, June 2017 (doi: 10.1109/EEE­IC.20­17.79­7­74­04).

[28]  S. Murali, R. Shankar, P. Aryan, “A novel optimization technique for LFC and virtual inertia emulation of a multi area hybrid power system”, Proceeding of the IEEE/ICEFEET, pp. 1-6, Patna, India , July 2020 (doi: 10.1109/ICEFEET49149.2020.9186998).

[29] A.X.R. Irudayaraj, N.I.A. Wahab, M.G. Umamaheswari, M.A.M. Radzi, N.B. Sulaiman, V. Veerasamy, S.C. Prasanna, R. Ramachandran, “A matignon’s theorem based stability analysis of hybrid power system for automatic load frequency control using atom search optimized FOPID controller”, IEEE Access, vol. 8, pp. 168751-168772, 2020 (doi: 10.1109/ACCESS.2020.3021212).

[30] D. Mohanty, S. Panda, “Robust frequency control of hybrid power system with EV and HP", Proceeding of t­he IEEE/ICEPE, pp. 1-5,  Shillong, Meghalaya, India, March 2021 (doi: 10.1109/ICEPE50861.2­021.94­0437­2­).

[31] H. Lund, W. Kempton, “Integration of renewable energy into the transport and electricity sectors through V2G”, Energy Policy, vol. 36, no. 9, pp. 3578-3587, Sept. 2008 (doi: 10.1016/j.enpol.2008.06.007).

[32] S.F. Aliabadi, S.A. Taher, M. Shahidehpour, “Smart deregulated grid frequency control in presence of renewable energy resources by EVs charging control", IEEE Trans. on Smart Grid, vol. 9, no. 2, pp. 1073-1085, March. 2018 (doi: 10.1109/TSG.2016.2575061).

[33] M.U. Jan, A. Xin, M.A. Abdelbaky, H.U. Rehman, S. Iqbal, “Adaptive and fuzzy PI controllers design for frequency regulation of isolated microgrid integrated with electric vehicles”, IEEE Access, vol. 8, pp. 87621-87632, Jan. 2020 (doi: 10.1109/ACCESS.2020.2993178).

[34] S. Amamra, J. Marco, “Vehicle-to-Grid aggregator to support power grid and reduce electric vehicle charging cost”, IEEE Access, vol. 7, pp. 178528-178538, 2019 (doi: 10.1109/ACCESS.2019.2958664).

[35] S. Kumar, K.K. Jaladi, “Grid connected electric vehicle charging station using PV source”, Proceeding of the IEEE/ICMICA, pp. 1-4, Kurukshetra, India, June 2020 (doi: 10.1109/ICMICA48462.2020.9242806).

[36]  A. Annamraju, S. Nandiraju, “Robust frequency control in a renewable penetrated power system: An adaptive fractional order-fuzzy approach'', Protection and Control of Modern Power Systems, vol. 4, no. 1, p. 16, Dec. 2019 (doi: 10.1186/s41601-019-0130-8).

[37] X. Liu, Y. Zhang, K.Y. Lee, “Coordinated distributed MPC for load frequency control of power system with wind farms'', IEEE Trans. on Industrial Electronics, vol. 64, no. 6, pp. 5140-5150, June 2017 (doi: 10.1109/ TIE.2016.2642882).

[38]  X. Kong, X. Liu, L. Ma, K.Y. Lee, “Hierarchical distributed model predictive control of standalone wind/solar/battery power system”, IEEE Trans. on Systems, Man, and Cybernetics, vol. 49, no. 8, pp. 1570-1581, Aug. 2019 (doi: 10.1109/TSMC.2019.2897646).

[39] W. Eshetu, P. Sharma, C. Sharma, “ANFIS based load frequency control in an isolated micro grid”, Procee­din­g of the IEEE/ICIT, pp. 1165-1170, Lyon, France, Feb. 2018 (doi: 10.1109/ICIT.201­8.8­352­343). 

[40] J. Yang, Z. Zeng, Y. Tang, J. Yan, H. He, Y. Wu, “Load frequency control in an isolated micro grid system with electric vehicles based on MGPT”, Energies, vol. 8, no. 3, pp. 2145-2164, Mar. 2015 (doi: 10.3390/en8­0321­4­5).

[41] J.S.R. Jang, “ANFIS: adaptive-network-based fuzzy inference system”, IEEE Trans. on Systems, Man, and Cybernetics, vol. 23, no. 3, pp. 665-685, May/June 1993 (doi: 10.1109/21.256541).

[42]  N. Mathur, I. Glesk, A. Buis “Comparison of adaptive neuro-fuzzy inference system (ANFIS) and Gaussian processes for machine learning (GPML) algorithms for the prediction of skin temperature in lower limb prostheses”,  Medical Engineering and Physics, vol. 38, no. 10, pp.‌ 1083-1089, Oct. 2016 )doi: org/10.1016/ j.medengphy. 2016.07.003).

[43] S. Prakash, A.K. Bhardwaj, S.K. Shinha “Neuro fuzzy hybrid intelligent approach for four-area load freq­ue­ncy control of interconnected power system”, Proceeding of the IEEE/ ICPCES, pp. 1-7, Allahabad, India, Dec. 2012 (doi: 10.1109/ICPCES.2012.6508124).

[44] C. Mu, Y. Tang, H. He, “Observer-based sliding mode frequency control for micro-grid with photovoltaic energy integration”, Proceeding of the IEEE/PESGM, pp. 1-5, Boston, MA, USA, July 2016 (doi: 10.110­9/PE­S­GM.2016.7742001).

[45]  M. Tavakoli, E. Pouresmaeil, J. Adabi, R. Godina, J.P.S. Catalão, “Load-frequency control in a  multi-source power system connected to wind farms through multi terminal HVDC systems”,  Computers and Operations Research, vol. 96, pp. 305-315, Aug. 2018 (doi: 10.1109/PESGM. 2016.7742001).